Analyzing Vital Sign Variability in Remote Monitoring as a Predictor of 31-Day Heart Failure Readmission: A Retrospective Cohort Study

Abstract

Introduction:

Heart failure (HF) is a major cause of morbidity and early hospital readmission in the United States. Remote patient monitoring (RPM) is increasingly used to support postdischarge care, but evidence remains mixed, and the prognostic value of day-to-day vital sign variability is unclear. This study evaluated whether physiologic variability and patient engagement during RPM were associated with 31-day HF readmission.

Methods:

A retrospective cohort study included 213 patients with HF enrolled in a postdischarge RPM program from June 2022 to April 2024. Patients recorded daily weight, blood pressure, and heart rate for up to 31 days after discharge. Vital sign variability metrics were generated by flagging days with threshold-crossing measurements and summarizing these fluctuations over the RPM monitoring period. Adjusted logistic regression models evaluated associations with 31-day HF readmission.

Results:

Pulse variability was significantly associated with 31-day readmission (OR 9.91, 95% CI 1.63–59.81, p = 0.011), while variability in weight and blood pressure showed no significant associations. Total vital sign variability also predicted readmission (OR 6.93, 95% CI 1.71–28.16, p = 0.007). Escalation outreach rate was strongly associated with readmission (OR 15.46, 95% CI 3.19–95.69, p = 0.001). Maximum brain natriuretic peptide values were higher among readmitted patients (p = 0.019).

Conclusion:

Variability in physiologic measures captured through remote monitoring, particularly pulse variability and overall fluctuation burden, may serve as clinically meaningful indicators of early decompensation. These findings highlight the potential value of dynamic RPM patterns in postdischarge risk assessment.